STAT41010

Relational data describe interactions between entities, and are readily available in a variety of data science contexts. Examples include social networks (e.g. professional or friendship ties between individuals), political and economic networks (e.g. relations and trades between countries), and biological networks (protein-protein interaction networks).

The study of relational data is impactful in a variety of applied fields. For example, we can use social networks to study the spread of a disease within a community; we can use economic networks to study financial stability; and biological networks may help in the development of new treatments.

Relational data are big data that are characterised by complex dependency structures, which are difficult to unravel and to summarise. This has led to the introduction of a number of methods and algorithms that address these challenges. This module covers the theory and methodologies that can be employed to model and study relational data.